Abstract: A method of geosteering in a wellbore construction process uses an earth model that defines boundaries between formation layers and petrophysical properties of the formation layers in a subterranean formation. Sensor measurements related to the wellbore construction process are inputted to the earth model. An estimate is obtained for a relative geometrical and geological placement of the well path with respect to a geological objective using a trained reinforcement learning agent. An output action based on the sensor measurement for influencing a future profile of the well path with respect to the estimate.

Abstract: A method for producing a simulation environment for training a function approximating agent uses an earth model that defines boundaries between formation layers and petrophysical properties of the formation layers in a subterranean formation. A toolface input corresponding to a set of model coefficients produced by the earth model is provided to a drilling attitude model, which produces a drill bit position. The drill bit position is fed to the earth model for determining an updated set of model coefficients for a predetermined interval and a set of signals representing physical properties of the subterranean formation. The signals are provided to a sensor model to produce at least one sensor output. A reward is determined from the sensor output. The simulation environment for training the function approximating agent can be used for automating a geosteering process.